1271 Repositories
Python global-models Libraries
Set of models for classifcation of 3D volumes
Classification models 3D Zoo - Keras and TF.Keras This repository contains 3D variants of popular CNN models for classification like ResNets, DenseNet
Code for pre-training CharacterBERT models (as well as BERT models).
Pre-training CharacterBERT (and BERT) This is a repository for pre-training BERT and CharacterBERT. DISCLAIMER: The code was largely adapted from an o
Official PyTorch implementation of MX-Font (Multiple Heads are Better than One: Few-shot Font Generation with Multiple Localized Experts)
Introduction Pytorch implementation of Multiple Heads are Better than One: Few-shot Font Generation with Multiple Localized Expert. | paper Song Park1
A collection of scripts to preprocess ASR datasets and finetune language-specific Wav2Vec2 XLSR models
wav2vec-toolkit A collection of scripts to preprocess ASR datasets and finetune language-specific Wav2Vec2 XLSR models This repository accompanies the
Source code for the GPT-2 story generation models in the EMNLP 2020 paper "STORIUM: A Dataset and Evaluation Platform for Human-in-the-Loop Story Generation"
Storium GPT-2 Models This is the official repository for the GPT-2 models described in the EMNLP 2020 paper [STORIUM: A Dataset and Evaluation Platfor
Code, Data and Demo for Paper: Controllable Generation from Pre-trained Language Models via Inverse Prompting
InversePrompting Paper: Controllable Generation from Pre-trained Language Models via Inverse Prompting Code: The code is provided in the "chinese_ip"
Official code for the CVPR 2021 paper "How Well Do Self-Supervised Models Transfer?"
How Well Do Self-Supervised Models Transfer? This repository hosts the code for the experiments in the CVPR 2021 paper How Well Do Self-Supervised Mod
(ImageNet pretrained models) The official pytorch implemention of the TPAMI paper "Res2Net: A New Multi-scale Backbone Architecture"
Res2Net The official pytorch implemention of the paper "Res2Net: A New Multi-scale Backbone Architecture" Our paper is accepted by IEEE Transactions o
Top2Vec is an algorithm for topic modeling and semantic search.
Top2Vec is an algorithm for topic modeling and semantic search. It automatically detects topics present in text and generates jointly embedded topic, document and word vectors.
Neural models of common sense. 🤖
Unicorn on Rainbow Neural models of common sense. This repository is for the paper: Unicorn on Rainbow: A Universal Commonsense Reasoning Model on a N
This project is part of Eleuther AI's quest to create a massive repository of high quality text data for training language models.
This project is part of Eleuther AI's quest to create a massive repository of high quality text data for training language models.
A novel method to tune language models. Codes and datasets for paper ``GPT understands, too''.
P-tuning A novel method to tune language models. Codes and datasets for paper ``GPT understands, too''. How to use our code We have released the code
Viewflow is an Airflow-based framework that allows data scientists to create data models without writing Airflow code.
Viewflow Viewflow is a framework built on the top of Airflow that enables data scientists to create materialized views. It allows data scientists to f
Automated Machine Learning Pipeline with Feature Engineering and Hyper-Parameters Tuning
The mljar-supervised is an Automated Machine Learning Python package that works with tabular data. I
A probabilistic programming library for Bayesian deep learning, generative models, based on Tensorflow
ZhuSuan is a Python probabilistic programming library for Bayesian deep learning, which conjoins the complimentary advantages of Bayesian methods and
A probabilistic programming language in TensorFlow. Deep generative models, variational inference.
Edward is a Python library for probabilistic modeling, inference, and criticism. It is a testbed for fast experimentation and research with probabilis
Describing statistical models in Python using symbolic formulas
Patsy is a Python library for describing statistical models (especially linear models, or models that have a linear component) and building design mat
A Python package for Bayesian forecasting with object-oriented design and probabilistic models under the hood.
Disclaimer This project is stable and being incubated for long-term support. It may contain new experimental code, for which APIs are subject to chang
Sensitivity Analysis Library in Python (Numpy). Contains Sobol, Morris, Fractional Factorial and FAST methods.
Sensitivity Analysis Library (SALib) Python implementations of commonly used sensitivity analysis methods. Useful in systems modeling to calculate the
Python Library for learning (Structure and Parameter) and inference (Statistical and Causal) in Bayesian Networks.
pgmpy pgmpy is a python library for working with Probabilistic Graphical Models. Documentation and list of algorithms supported is at our official sit
Fast, flexible and easy to use probabilistic modelling in Python.
Please consider citing the JMLR-MLOSS Manuscript if you've used pomegranate in your academic work! pomegranate is a package for building probabilistic
Hidden Markov Models in Python, with scikit-learn like API
hmmlearn hmmlearn is a set of algorithms for unsupervised learning and inference of Hidden Markov Models. For supervised learning learning of HMMs and
Scikit-learn compatible estimation of general graphical models
skggm : Gaussian graphical models using the scikit-learn API In the last decade, learning networks that encode conditional independence relationships
Differentiable SDE solvers with GPU support and efficient sensitivity analysis.
PyTorch Implementation of Differentiable SDE Solvers This library provides stochastic differential equation (SDE) solvers with GPU support and efficie
Pretrained EfficientNet, EfficientNet-Lite, MixNet, MobileNetV3 / V2, MNASNet A1 and B1, FBNet, Single-Path NAS
(Generic) EfficientNets for PyTorch A 'generic' implementation of EfficientNet, MixNet, MobileNetV3, etc. that covers most of the compute/parameter ef
Rembg Video Virtual Green Screen Edition
Rembg Virtual Greenscreen Edition is a tool to create a green screen matte for videos
Decentralized deep learning in PyTorch. Built to train models on thousands of volunteers across the world.
Hivemind: decentralized deep learning in PyTorch Hivemind is a PyTorch library to train large neural networks across the Internet. Its intended usage
Petastorm library enables single machine or distributed training and evaluation of deep learning models from datasets in Apache Parquet format. It supports ML frameworks such as Tensorflow, Pytorch, and PySpark and can be used from pure Python code.
Petastorm Contents Petastorm Installation Generating a dataset Plain Python API Tensorflow API Pytorch API Spark Dataset Converter API Analyzing petas
AtsPy: Automated Time Series Models in Python (by @firmai)
Automated Time Series Models in Python (AtsPy) SSRN Report Easily develop state of the art time series models to forecast univariate data series. Simp
Automatically build ARIMA, SARIMAX, VAR, FB Prophet and XGBoost Models on Time Series data sets with a Single Line of Code. Now updated with Dask to handle millions of rows.
Auto_TS: Auto_TimeSeries Automatically build multiple Time Series models using a Single Line of Code. Now updated with Dask. Auto_timeseries is a comp
A python library for easy manipulation and forecasting of time series.
Time Series Made Easy in Python darts is a python library for easy manipulation and forecasting of time series. It contains a variety of models, from
A statistical library designed to fill the void in Python's time series analysis capabilities, including the equivalent of R's auto.arima function.
pmdarima Pmdarima (originally pyramid-arima, for the anagram of 'py' + 'arima') is a statistical library designed to fill the void in Python's time se
ARCH models in Python
arch Autoregressive Conditional Heteroskedasticity (ARCH) and other tools for financial econometrics, written in Python (with Cython and/or Numba used
Qlib is an AI-oriented quantitative investment platform, which aims to realize the potential, empower the research, and create the value of AI technologies in quantitative investment. With Qlib, you can easily try your ideas to create better Quant investment strategies.
Qlib is an AI-oriented quantitative investment platform, which aims to realize the potential, empower the research, and create the value of AI technol
Source code, datasets and trained models for the paper Learning Advanced Mathematical Computations from Examples (ICLR 2021), by François Charton, Amaury Hayat (ENPC-Rutgers) and Guillaume Lample
Maths from examples - Learning advanced mathematical computations from examples This is the source code and data sets relevant to the paper Learning a
Diverse Image Captioning with Context-Object Split Latent Spaces (NeurIPS 2020)
Diverse Image Captioning with Context-Object Split Latent Spaces This repository is the PyTorch implementation of the paper: Diverse Image Captioning
CDIoU and CDIoU loss is like a convenient plug-in that can be used in multiple models. CDIoU and CDIoU loss have different excellent performances in several models such as Faster R-CNN, YOLOv4, RetinaNet and . There is a maximum AP improvement of 1.9% and an average AP of 0.8% improvement on MS COCO dataset, compared to traditional evaluation-feedback modules. Here we just use as an example to illustrate the code.
CDIoU-CDIoUloss CDIoU and CDIoU loss is like a convenient plug-in that can be used in multiple models. CDIoU and CDIoU loss have different excellent p
⚡ boost inference speed of T5 models by 5x & reduce the model size by 3x using fastT5.
Reduce T5 model size by 3X and increase the inference speed up to 5X. Install Usage Details Functionalities Benchmarks Onnx model Quantized onnx model
Monocular Depth Estimation - Weighted-average prediction from multiple pre-trained depth estimation models
merged_depth runs (1) AdaBins, (2) DiverseDepth, (3) MiDaS, (4) SGDepth, and (5) Monodepth2, and calculates a weighted-average per-pixel absolute dept
Repository providing a wide range of self-supervised pretrained models for computer vision tasks.
Hierarchical Pretraining: Research Repository This is a research repository for reproducing the results from the project "Self-supervised pretraining
This repository lets you train neural networks models for performing end-to-end full-page handwriting recognition using the Apache MXNet deep learning frameworks on the IAM Dataset.
Handwritten Text Recognition (OCR) with MXNet Gluon These notebooks have been created by Jonathan Chung, as part of his internship as Applied Scientis
TensorFlow code for the neural network presented in the paper: "Structural Language Models of Code" (ICML'2020)
SLM: Structural Language Models of Code This is an official implementation of the model described in: "Structural Language Models of Code" [PDF] To ap
中文语音识别系列,读者可以借助它快速训练属于自己的中文语音识别模型,或直接使用预训练模型测试效果。
MASR中文语音识别(pytorch版) 开箱即用 自行训练 使用与训练分离(增量训练) 识别率高 说明:因为每个人电脑机器不同,而且有些安装包安装起来比较麻烦,强烈建议直接用我编译好的docker环境跑 目前docker基础环境为ubuntu-cuda10.1-cudnn7-pytorch1.6.
(under submission) Bayesian Integration of a Generative Prior for Image Restoration
BIGPrior: Towards Decoupling Learned Prior Hallucination and Data Fidelity in Image Restoration Authors: Majed El Helou, and Sabine Süsstrunk {Note: p
Deep generative modeling for time-stamped heterogeneous data, enabling high-fidelity models for a large variety of spatio-temporal domains.
Neural Spatio-Temporal Point Processes [arxiv] Ricky T. Q. Chen, Brandon Amos, Maximilian Nickel Abstract. We propose a new class of parameterizations
🦉Data Version Control | Git for Data & Models
Website • Docs • Blog • Twitter • Chat (Community & Support) • Tutorial • Mailing List Data Version Control or DVC is an open-source tool for data sci
Code for ICLR 2021 Paper, "Anytime Sampling for Autoregressive Models via Ordered Autoencoding"
Anytime Autoregressive Model Anytime Sampling for Autoregressive Models via Ordered Autoencoding , ICLR 21 Yilun Xu, Yang Song, Sahaj Gara, Linyuan Go
Beyond the Imitation Game collaborative benchmark for enormous language models
BIG-bench 🪑 The Beyond the Imitation Game Benchmark (BIG-bench) will be a collaborative benchmark intended to probe large language models, and extrap
Scripts of Machine Learning Algorithms from Scratch. Implementations of machine learning models and algorithms using nothing but NumPy with a focus on accessibility. Aims to cover everything from basic to advance.
Algo-ScriptML Python implementations of some of the fundamental Machine Learning models and algorithms from scratch. The goal of this project is not t
Django project starter on steroids: quickly create a Django app AND generate source code for data models + REST/GraphQL APIs (the generated code is auto-linted and has 100% test coverage).
Create Django App 💛 We're a Django project starter on steroids! One-line command to create a Django app with all the dependencies auto-installed AND
Code associated with the "Data Augmentation using Pre-trained Transformer Models" paper
Data Augmentation using Pre-trained Transformer Models Code associated with the Data Augmentation using Pre-trained Transformer Models paper Code cont
MMdnn is a set of tools to help users inter-operate among different deep learning frameworks. E.g. model conversion and visualization. Convert models between Caffe, Keras, MXNet, Tensorflow, CNTK, PyTorch Onnx and CoreML.
MMdnn MMdnn is a comprehensive and cross-framework tool to convert, visualize and diagnose deep learning (DL) models. The "MM" stands for model manage
library for nonlinear optimization, wrapping many algorithms for global and local, constrained or unconstrained, optimization
NLopt is a library for nonlinear local and global optimization, for functions with and without gradient information. It is designed as a simple, unifi
A research toolkit for particle swarm optimization in Python
PySwarms is an extensible research toolkit for particle swarm optimization (PSO) in Python. It is intended for swarm intelligence researchers, practit
A Python implementation of global optimization with gaussian processes.
Bayesian Optimization Pure Python implementation of bayesian global optimization with gaussian processes. PyPI (pip): $ pip install bayesian-optimizat
A library for hidden semi-Markov models with explicit durations
hsmmlearn hsmmlearn is a library for unsupervised learning of hidden semi-Markov models with explicit durations. It is a port of the hsmm package for
Scikit-learn compatible estimation of general graphical models
skggm : Gaussian graphical models using the scikit-learn API In the last decade, learning networks that encode conditional independence relationships
Visualizer for neural network, deep learning, and machine learning models
Netron is a viewer for neural network, deep learning and machine learning models. Netron supports ONNX (.onnx, .pb, .pbtxt), Keras (.h5, .keras), Tens
Interpretability and explainability of data and machine learning models
AI Explainability 360 (v0.2.1) The AI Explainability 360 toolkit is an open-source library that supports interpretability and explainability of datase
FairML - is a python toolbox auditing the machine learning models for bias.
======== FairML: Auditing Black-Box Predictive Models FairML is a python toolbox auditing the machine learning models for bias. Description Predictive
Algorithms for monitoring and explaining machine learning models
Alibi is an open source Python library aimed at machine learning model inspection and interpretation. The focus of the library is to provide high-qual
Ludwig is a toolbox that allows to train and evaluate deep learning models without the need to write code.
Translated in 🇰🇷 Korean/ Ludwig is a toolbox that allows users to train and test deep learning models without the need to write code. It is built on
📝 Wrapper library for text generation / language models at char and word level with RNN in TensorFlow
tensorlm Generate Shakespeare poems with 4 lines of code. Installation tensorlm is written in / for Python 3.4+ and TensorFlow 1.1+ pip3 install tenso
Datasets, Transforms and Models specific to Computer Vision
torchvision The torchvision package consists of popular datasets, model architectures, and common image transformations for computer vision. Installat
Probabilistic programming framework that facilitates objective model selection for time-varying parameter models.
Time series analysis today is an important cornerstone of quantitative science in many disciplines, including natural and life sciences as well as eco
[HELP REQUESTED] Generalized Additive Models in Python
pyGAM Generalized Additive Models in Python. Documentation Official pyGAM Documentation: Read the Docs Building interpretable models with Generalized
Highly interpretable classifiers for scikit learn, producing easily understood decision rules instead of black box models
Highly interpretable, sklearn-compatible classifier based on decision rules This is a scikit-learn compatible wrapper for the Bayesian Rule List class
50% faster, 50% less RAM Machine Learning. Numba rewritten Sklearn. SVD, NNMF, PCA, LinearReg, RidgeReg, Randomized, Truncated SVD/PCA, CSR Matrices all 50+% faster
[Due to the time taken @ uni, work + hell breaking loose in my life, since things have calmed down a bit, will continue commiting!!!] [By the way, I'm
OpenChat: Opensource chatting framework for generative models
OpenChat is opensource chatting framework for generative models.
A Python library that helps data scientists to infer causation rather than observing correlation.
A Python library that helps data scientists to infer causation rather than observing correlation.
A wiki system with complex functionality for simple integration and a superb interface. Store your knowledge with style: Use django models.
django-wiki Django support The below table explains which Django versions are supported. Release Django Upgrade from 0.7.x 2.2, 3.0, 3.1 0.5 or 0.6 0.
🦉Data Version Control | Git for Data & Models
Website • Docs • Blog • Twitter • Chat (Community & Support) • Tutorial • Mailing List Data Version Control or DVC is an open-source tool for data sci
Admin Panel for GinoORM - ready to up & run (just add your models)
Gino-Admin Docs (state: in process): Gino-Admin docs Play with Demo (current master 0.2.3) Gino-Admin demo (login: admin, pass: 1234) Admin
FastAPI Skeleton App to serve machine learning models production-ready.
FastAPI Model Server Skeleton Serving machine learning models production-ready, fast, easy and secure powered by the great FastAPI by Sebastián Ramíre
Release for Improved Denoising Diffusion Probabilistic Models
improved-diffusion This is the codebase for Improved Denoising Diffusion Probabilistic Models. Usage This section of the README walks through how to t
Hook and simulate global keyboard events on Windows and Linux.
keyboard Take full control of your keyboard with this small Python library. Hook global events, register hotkeys, simulate key presses and much more.
BitPack is a practical tool to efficiently save ultra-low precision/mixed-precision quantized models.
BitPack is a practical tool that can efficiently save quantized neural network models with mixed bitwidth.
Reviving Iterative Training with Mask Guidance for Interactive Segmentation
This repository provides the source code for training and testing state-of-the-art click-based interactive segmentation models with the official PyTorch implementation
ForecastGA is a Python tool to forecast Google Analytics data using several popular time series models.
ForecastGA is a tool that combines a couple of popular libraries, Atspy and googleanalytics, with a few enhancements.
Pre-trained NFNets with 99% of the accuracy of the official paper
NFNet Pytorch Implementation This repo contains pretrained NFNet models F0-F6 with high ImageNet accuracy from the paper High-Performance Large-Scale
FastAPI Skeleton App to serve machine learning models production-ready.
FastAPI Model Server Skeleton Serving machine learning models production-ready, fast, easy and secure powered by the great FastAPI by Sebastián Ramíre
Facilitating the design, comparison and sharing of deep text matching models.
MatchZoo Facilitating the design, comparison and sharing of deep text matching models. MatchZoo 是一个通用的文本匹配工具包,它旨在方便大家快速的实现、比较、以及分享最新的深度文本匹配模型。 🔥 News
🏖 Easy training and deployment of seq2seq models.
Headliner Headliner is a sequence modeling library that eases the training and in particular, the deployment of custom sequence models for both resear
Sequence-to-sequence framework with a focus on Neural Machine Translation based on Apache MXNet
Sockeye This package contains the Sockeye project, an open-source sequence-to-sequence framework for Neural Machine Translation based on Apache MXNet
:house_with_garden: Fast & easy transfer learning for NLP. Harvesting language models for the industry. Focus on Question Answering.
(Framework for Adapting Representation Models) What is it? FARM makes Transfer Learning with BERT & Co simple, fast and enterprise-ready. It's built u
Super easy library for BERT based NLP models
Fast-Bert New - Learning Rate Finder for Text Classification Training (borrowed with thanks from https://github.com/davidtvs/pytorch-lr-finder) Suppor
A full spaCy pipeline and models for scientific/biomedical documents.
This repository contains custom pipes and models related to using spaCy for scientific documents. In particular, there is a custom tokenizer that adds
A framework for training and evaluating AI models on a variety of openly available dialogue datasets.
ParlAI (pronounced “par-lay”) is a python framework for sharing, training and testing dialogue models, from open-domain chitchat, to task-oriented dia
State of the Art Natural Language Processing
Spark NLP: State of the Art Natural Language Processing Spark NLP is a Natural Language Processing library built on top of Apache Spark ML. It provide
🤗Transformers: State-of-the-art Natural Language Processing for Pytorch and TensorFlow 2.0.
State-of-the-art Natural Language Processing for PyTorch and TensorFlow 2.0 🤗 Transformers provides thousands of pretrained models to perform tasks o
The open-source tool for building high-quality datasets and computer vision models
The open-source tool for building high-quality datasets and computer vision models. Website • Docs • Try it Now • Tutorials • Examples • Blog • Commun
Inner ear models for Python
cochlea cochlea is a collection of inner ear models. All models are easily accessible as Python functions. They take sound signal as input and return
Neural building blocks for speaker diarization: speech activity detection, speaker change detection, overlapped speech detection, speaker embedding
⚠️ Checkout develop branch to see what is coming in pyannote.audio 2.0: a much smaller and cleaner codebase Python-first API (the good old pyannote-au
NO LONGER MAINTAINED - A Flask extension for creating simple ReSTful JSON APIs from SQLAlchemy models.
NO LONGER MAINTAINED This repository is no longer maintained due to lack of time. You might check out the fork https://github.com/mrevutskyi/flask-res
TransGAN: Two Transformers Can Make One Strong GAN
[Preprint] "TransGAN: Two Transformers Can Make One Strong GAN", Yifan Jiang, Shiyu Chang, Zhangyang Wang
Python scripts to detect faces in Python with the BlazeFace Tensorflow Lite models
Python scripts to detect faces using Python with the BlazeFace Tensorflow Lite models. Tested on Windows 10, Tensorflow 2.4.0 (Python 3.8).
A dynamic FastAPI router that automatically creates CRUD routes for your models
⚡ Create CRUD routes with lighting speed ⚡ A dynamic FastAPI router that automatically creates CRUD routes for your models Documentation: https://fast
A tool to convert AWS EC2 instances back and forth between On-Demand and Spot billing models.
ec2-spot-converter This tool converts existing AWS EC2 instances back and forth between On-Demand and 'persistent' Spot billing models while preservin
Simple SDF mesh generation in Python
Generate 3D meshes based on SDFs (signed distance functions) with a dirt simple Python API.